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Concept-oriented video skimming and adaptation via semantic classification

Published: 15 October 2004 Publication History

Abstract

Concept-oriented video skimming and adaptation plays an important role in enabling online medical education by selecting and transmitting the suitable medical video clips to the students over network. In this paper, we propose a novel framework to enable concept-oriented video skimming and adaptation in a specific domain of medical education video. Specifically, this framework includes: (a) A novel semantic-sensitive framework for video content characterization and representation by using principal video shots to enhance the quality of features on discriminating between different semantic video concepts. (b) A novel technique for semantic medical concept interpretation by using finite mixture models to approximate the class distributions of the relevant principal video shots. (c) A novel classifier training scheme by using an adaptive Expectation-Maximization (EM) algorithm for automatic parameter estimation and model selection (i.e., selecting the optimal number of mixture Gaussian components). (d) Subjective driven concept-oriented video skimming algorithm via semantic video classification

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  • (2018)Multimedia news exploration and retrieval by integrating keywords, relations and visual featuresMultimedia Tools and Applications10.1007/s11042-010-0639-351:2(625-648)Online publication date: 31-Dec-2018
  • (2012)Video Summarization and Significance of ContentHandbook on Soft Computing for Video Surveillance10.1201/b11631-5(79-102)Online publication date: 2-Mar-2012
  • (2007)Large scale news video database browsing and retrieval via information visualizationProceedings of the 2007 ACM symposium on Applied computing10.1145/1244002.1244238(1086-1087)Online publication date: 11-Mar-2007
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    cover image ACM Conferences
    MIR '04: Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
    October 2004
    334 pages
    ISBN:1581139403
    DOI:10.1145/1026711
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 15 October 2004

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    1. concept-oriented video skimming and adaptation
    2. semantic video classification

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    View all
    • (2018)Multimedia news exploration and retrieval by integrating keywords, relations and visual featuresMultimedia Tools and Applications10.1007/s11042-010-0639-351:2(625-648)Online publication date: 31-Dec-2018
    • (2012)Video Summarization and Significance of ContentHandbook on Soft Computing for Video Surveillance10.1201/b11631-5(79-102)Online publication date: 2-Mar-2012
    • (2007)Large scale news video database browsing and retrieval via information visualizationProceedings of the 2007 ACM symposium on Applied computing10.1145/1244002.1244238(1086-1087)Online publication date: 11-Mar-2007
    • (2007)Ontology Specification and Integration for Multimedia ApplicationsOntologies10.1007/978-0-387-37022-4_9(265-296)Online publication date: 2007
    • (2006)Using Multimedia Ontology for Generating Conceptual Annotations and Hyperlinks in Video CollectionsProceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence10.1109/WI.2006.183(211-217)Online publication date: 18-Dec-2006
    • (2006)Techniques for movie content analysis and skimming: tutorial and overview on video abstraction techniquesIEEE Signal Processing Magazine10.1109/MSP.2006.162145123:2(79-89)Online publication date: Mar-2006

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